snipara-mcp

snipara-mcp

Lightweight MCP connector that provides persistent project memory and context optimization for AI agents via Snipara's hosted APIs.

Category
Visit Server

README

snipara-mcp

PyPI version Python 3.10+ License: MIT

snipara-mcp is the lightweight MCP connector for Snipara.

Memory belongs to the project, not the model.

Use it when an MCP client needs a local stdio process that talks to Snipara's hosted project memory and context optimization APIs.

What Is Snipara?

Snipara is project-scoped persistent context for AI-assisted work.

It gives Claude Code, Cursor, Codex, OpenAI Agents, and other MCP-compatible clients a shared memory layer that survives sessions, users, tools, and model switches.

Your agent still uses its own LLM. Snipara gives it the right context.

Why MCP?

MCP is becoming a standard adapter layer for agent tools. snipara-mcp makes Snipara available through that layer without forcing developers into a specific IDE, model, or orchestration framework.

The integration should feel small:

uvx snipara-mcp

The impact is larger: agents can retrieve durable project context instead of starting cold every session.

Architecture

Claude Code       Cursor          Codex          OpenAI Agents
    |               |              |                  |
    +---------------+--------------+------------------+
                    |
             snipara-mcp
                    |
        Hosted Snipara MCP API
                    |
          Shared Project Memory
                    |
        Compact Context for Your LLM

Hosted HTTP Or Stdio?

Use the hosted HTTP endpoint when your MCP client supports streamable HTTP:

{
  "mcpServers": {
    "snipara": {
      "type": "http",
      "url": "https://api.snipara.com/mcp/your-project-id-or-slug",
      "headers": {
        "Authorization": "Bearer rlm_your_api_key"
      }
    }
  }
}

Use snipara-mcp when your client expects a local stdio command:

{
  "mcpServers": {
    "snipara": {
      "command": "uvx",
      "args": ["snipara-mcp"],
      "env": {
        "SNIPARA_API_KEY": "rlm_your_api_key",
        "SNIPARA_PROJECT_ID": "your-project-id-or-slug"
      }
    }
  }
}

Install

No local install:

uvx snipara-mcp

Python package:

pip install snipara-mcp

With RLM Runtime helper integration:

pip install "snipara-mcp[rlm]"

Quickstart

Sign in through the browser:

pip install snipara-mcp
snipara login

Initialize a project:

snipara init

The initializer detects common project files, writes MCP configuration, and can upload local project docs when you are authenticated.

Useful options:

snipara init --slug my-project
snipara init --dry-run
snipara init --no-upload
snipara init --skip-test

Claude Code

claude mcp add snipara -- uvx snipara-mcp

Then export credentials in your shell:

export SNIPARA_API_KEY="rlm_your_api_key"
export SNIPARA_PROJECT_ID="your-project-id-or-slug"

Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "snipara": {
      "command": "uvx",
      "args": ["snipara-mcp"],
      "env": {
        "SNIPARA_API_KEY": "rlm_your_api_key",
        "SNIPARA_PROJECT_ID": "your-project-id-or-slug"
      }
    }
  }
}

Environment

Variable Required Description
SNIPARA_API_KEY Yes, unless using snipara login Snipara API key
SNIPARA_PROJECT_ID Yes, unless using SNIPARA_PROJECT_SLUG Project identifier
SNIPARA_PROJECT_SLUG Yes, unless using SNIPARA_PROJECT_ID Project slug
SNIPARA_API_URL No Defaults to https://api.snipara.com

OAuth tokens created by snipara login are stored in ~/.snipara/tokens.json. If a project id or slug is set, the connector selects the matching token and does not silently fall back to another project.

What You Get

The connector exposes the same MCP contract as the hosted backend. The packaged tool surface is generated from the server source of truth.

Common tool groups:

  • retrieval: rlm_context_query, rlm_search, rlm_get_chunk, rlm_load_document
  • durable memory: rlm_recall, rlm_remember, rlm_memory_compact
  • shared context: rlm_shared_context, collection and template tools
  • document upload: rlm_upload_document, rlm_sync_documents
  • project setup: client, project, and business-context workspace tools
  • operations: rlm_settings, rlm_index_health, rlm_reindex
  • code graph: rlm_code_* tools when code indexes are available
  • coordination: swarm, hierarchical task, and state tools when enabled

Tool availability can vary by plan, hosted deployment, and project index state.

CLI Commands

Command Description
snipara login Browser login and token setup
snipara init Initialize Snipara in the current project
snipara logout Clear stored tokens
snipara status Show auth and project status
snipara-mcp Run the MCP stdio server

Legacy aliases such as snipara-init, snipara-mcp-login, snipara-mcp-logout, and snipara-mcp-status are still supported.

Relationship To Other Repos

Repo Role
Snipara/snipara-server Hosted and self-hosted server surface
alopez3006/snipara-mcp This stdio connector package
Snipara/snipara-memory Open memory primitives and schema

snipara-mcp is intentionally thin. It should be easy to install, easy to audit, and boring to operate. The heavy lifting stays in Snipara's hosted context and memory engine.

Development

pip install -e ".[dev]"
pytest
ruff check .

The source of truth for the generated tool contract lives in the Snipara server. When backend tools change, regenerate the packaged contract before publishing this package.

License

MIT. See LICENSE.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured